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•
If we draw a random sample from a normal distribution population:
o
The sample mean is
not
equal to the sample median
o
The sample mean is
not
always equal to the population mean
o
The sample variance is
not
always larger than the population variance
•
If the correlation coefficient of two random variables x and y is zero, then
o
X and y are
not
independent
o
E(XY) is equal to E(X) x E(Y)
•
For the sampling distribution of the sample mean xbar:
o
Mu of xbar is equal to mu of population
o
Xbar does not always follow a normal distribution
•
Changing the sample size or increasing the significance level cannot make the power and
P(Type II error) both increase
•
The Central Limit Theorem says that the distribution of xbar will be approximately
normal given a large sample size and a normal population distribution
•
Greater confidence level, greater standard deviation, and smaller sample size all increase
the width of the confidence interval
•
For a Studentt distribution, it is
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This note was uploaded on 10/02/2008 for the course STAT 212 taught by Professor Holt during the Spring '08 term at UVA.
 Spring '08
 HOLT
 Normal Distribution, Variance

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